A recurrent error propagation network speech recognition system
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[1] S. Young. Competitive training in hidden Markov models , 1990 .
[2] Hervé Bourlard,et al. Continuous speech recognition using multilayer perceptrons with hidden Markov models , 1990, International Conference on Acoustics, Speech, and Signal Processing.
[3] Mei-Yuh Hwang,et al. Recent progress and future outlook of the SPHINX speech recognition system , 1990 .
[4] John Holdsworth,et al. A comparison of preprocessors for the cambridge recurrent error propagation network speech recognition system , 1990, ICSLP.
[5] Hsiao-Wuen Hon,et al. Speaker-independent phone recognition using hidden Markov models , 1989, IEEE Trans. Acoust. Speech Signal Process..
[6] Michael Witbrock,et al. A connectionist approach to continuous speech recognition , 1989, International Conference on Acoustics, Speech, and Signal Processing,.
[7] Richard Lippmann,et al. Review of Neural Networks for Speech Recognition , 1989, Neural Computation.
[8] Stephen E. Levinson,et al. Speaker independent phonetic transcription of fluent speech for large vocabulary speech recognition , 1989, International Conference on Acoustics, Speech, and Signal Processing,.
[9] Esther Levin,et al. Accelerated Learning in Layered Neural Networks , 1988, Complex Syst..
[10] Patti Price,et al. The DARPA 1000-word resource management database for continuous speech recognition , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.
[11] Robert A. Jacobs,et al. Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.
[12] Frank Fallside,et al. An adaptive training algorithm for back propagation networks , 1987 .
[13] Eric B. Baum,et al. Supervised Learning of Probability Distributions by Neural Networks , 1987, NIPS.
[14] Lalit R. Bahl,et al. Maximum mutual information estimation of hidden Markov model parameters for speech recognition , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.
[15] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[16] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[17] L. Rabiner,et al. An introduction to hidden Markov models , 1986, IEEE ASSP Magazine.
[18] Hermann Ney,et al. The use of a one-stage dynamic programming algorithm for connected word recognition , 1984 .
[19] L. R. Rabiner,et al. An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition , 1983, The Bell System Technical Journal.
[20] L. R. Rabiner,et al. On the application of vector quantization and hidden Markov models to speaker-independent, isolated word recognition , 1983, The Bell System Technical Journal.
[21] B. Lindblom,et al. Modeling the judgment of vowel quality differences. , 1981, The Journal of the Acoustical Society of America.